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Gladen
@lyubo_p
Doing whatever needs doing @Extendedapp Views my own. Info only. No advice, offer or solicitation. Not for persons in restricted jurisdictions.
264 Following    295 Followers
State of liquidity and execution on @extendedapp v5 - TradFi Edition By popular demand, we're taking our liquidity analysis beyond crypto for the first time, this time covering TradFi markets: US equities (NVDA, MSTR, INTC, CRCL), precious metals (XAU, XAG), and the Nasdaq Index (NDX), across @extendedapp, @HyperliquidX (via @tradexyz), and @Lighter_xyz. Methodology 1. We measured slippage (buy/sell) on the above assets for $10k and $100k market orders across the three exchanges every 30 seconds from Mar 24, 07:11 UTC to Mar 31, 11:44 UTC (20,657 snapshots) 2. We ranked each exchange by market and clip size for both slippage and total cost of execution (slippage + exchange fee), where 1 = best and 3 = worst 3. Fees applied: Extended 2.5 bps, Hyperliquid base rate 4.5 bps, Lighter 0 bps 4. The dataset also includes charts showing how slippage evolved over the tracked period 5. NDX is listed as XYZ100 on Hyperliquid and QQQ on Lighter Results: Slippage - On equities and metals, Extended leads at $10k clip sizes, while Hyperliquid is better at $100k - On indices (NDX), Hyperliquid leads at both clip sizes Total cost of execution - where it gets interesting - Equities at $10k: Extended is the cheapest across all 4 - Equities at $100k: Hyperliquid leads across all 4 - Metals: Lighter's zero-fee model gives it the edge on both XAU and XAG at $10k, and on XAU at $100k - Indices (NDX): Hyperliquid leads at both clip sizes What this means 1. For equity trading at smaller sizes, Extended liquidity and fee structure make it the most efficient option overall 2. For larger orders, Hyperliquid has deeper liquidity and wins on total cost 3. Lighter's zero-fee model gives it a real edge in metals, though less so in equities It’s still early days for on-chain TradFi liquidity. There’s room for all exchanges to improve, and we'll keep tracking it. Full dataset:
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